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Our research was recently highlighted! (click to link) (This appeared in: International Innovation)

Nature provides a vast collection of biological systems which have evolved mechanisms to achieve catalysis, regulation, molecular recognition, and energy utilization with incredible efficiency. Our ability to successfully re-design and harness such systems is integral to realizing a future of cost-effective "green" chemistry, renewable fuels and chemicals, bioremediation, and "next-generation" therapeutics.

Research in the Cirino laboratory interfaces Chemical Engineering with the biological sciences, with emphases in biomolecular engineering, metabolic engineering, and biocatalysis. Recent research efforts are summarized in the poster presentations below (right click to view larger images). By applying biological design principles at the molecular level (e.g., engineer proteins) as well as the systems level (e.g., engineer metabolic pathways and gene regulation) we are creating novel microbial strains with improved biocatalytic efficiency (e.g. increased supply of NADPH to transformations of interest), and we are designing novel biosensors by customizing regulatory proteins, with broad applications in synthetic biology and biocatalyst development.

Protein Engineering/Molecular Recognition

We are using combinatorial (evolutionary) as well as rational (structure-based) protein design techniques to engineer transcriptional regulatory proteins to serve as customized biosensors. These proteins are being designed to recognize specific non-native molecules of interest ("effectors") and report their presence and concentration by regulating expression of a reporter gene. Such endogenous biosensors serve as powerful tools in synthetic biology and facilitate subsequent protein engineering and metabolic engineering efforts in our lab and others.

(Click to view a larger image)

Metabolic Engineering

Metabolic engineering is defined as the improvement of cellular activities by manipulation of enzymatic, transport, and regulatory functions of the cell with the use of recombinant DNA technology. Current research in our lab is aimed at modifying microbial metabolism to carry out new or improved bioconversions for the production of various secondary metabolites. This typically requires expression of foreign genes in an amenable microbial host (e.g. E. coli). Several stages of genetic optimization are then required to improve efficiency and productivity. As strategies to improve strain performance parameters are developed and tested, we gain new insights into microbial metabolism and physiology, further informing the design process.

In one example, we engineer the metabolism of E. coli to create biocatalytic strains which maximize yields on reducing equivalents in the form of NADPH, derived from renewable biomass sugars. This reducing power is subsequently channeled away from aerobic respiration and into driving reactions of interest, such as the reduction of xylose to xylitol (a sweetener and synthetic building block molecule).

In other examples, we are improving flux of precursors metabolites (e.g. acetyl-CoA and malonyl-CoA) toward the synthesis of secondary metabolites (natural products such as polyketides and isoprenoids) by genetically modified bacteria. This is largely accomplished via a "directed evolution" strategy in which large numbers of genetic variants are created and screened for improved properties. This in turn requires high throughput screening of target compounds, which we achieve by creating customized molecular reporters derived from natural regulatory proteins.

Additional projects include engineering oxygenase enzymes to accommodate new or improved activities, and implementing our custom-designed regulatory proteins in high-throughput screening of novel enzyme and microbial biocatalysts (see above). All research projects draw from a broad base of knowledge and experimental techniques spanning many disciplines, the common goal being that we use biology to solve problems pertinent to the expanding field of Chemical Engineering.

Computation and modeling contribute to many areas of our research by reducing experimental variables and guiding experimental efforts. Likewise, experimental results can provide information leading to improved biological models. This complementary exchange of information is realized through collaborations with Dr. Costas Maranas at Penn State University.